For many companies, it is desirable to forecast the financial future of a product or service offered by the company. For example, a company may want to know the approximate change in future sales, growth, and profit of the product or service. In addition, many companies want to know the effects of changes in causal events (e.g., marketing, advertising, and/or pricing changes) on forecasted data (e.g., sales volume, growth, and/or profit) and how these changes affect future of the offered product or service. As a result, many companies use a forecast model encompassing many pieces of causal data to predict forecasted data.
To obtain a forecast model, companies hire a marketing scientist or firm to create a new forecast model from previously collected data (causal and dependent). As time progresses and situations in the company and its atmosphere change, the created forecast model becomes less reliable and thus out of date. Therefore, many companies will ask the scientist or firm to create a new model every one or two years.
One problem with periodically creating a new model is the cost associated with creating a new model. Creating a new forecast model is extremely resource (e.g., computer resources) and time intensive. As a result, the cost of creating a new forecast model can be prohibitive for many companies.
Another problem is that the forecast models may become inaccurate over time, and thus become unable to forecast changes in demand for products or services under time sensitive or new marketing operations. For example, a medium for advertising that has not before been entered by a company would not be handled well by the forecast model in predicting the new medium's effectiveness for advertising. In a specific example, a new advertising medium beginning to take shape is advertising on online game arcade websites or within video games sold for PC's and console machines (e.g., Microsoft's® Xbox360® and Sony's® Playstation® series). If Coca-Cola® wishes to pursue the possibility of advertising in an upcoming Xbox360® game and has only recently begun advertising in other games (i.e., after the last forecast model was created), then the forecast model would not be able to predict the effectiveness of advertising in the upcoming Xbox360® game.
Another problem is that use of an older forecast model diminishes the confidence of the user and company in the forecast model's results. Thus, greater indecisiveness in marketing decisions could be created through the growing mistrust in the older forecast model.
Therefore, what is needed is an apparatus and method for updating an existing forecast model.